The presence of undesired signals is a concern in the processing of virtually all electromagnetic signals. Even in a relatively simple system, such as a radio, a squelch control is often provided to attenuate signals below a certain magnitude, so as to avoid undesired background static being audible when a signal of interest is not being received. What constitutes undesired background static is for the user to judge, and the user can set the squelch control to limit the audibility of received signals based on the user's judgment.
Automated signal processing systems, where a computer system autonomously responds to input signals, present a more difficult problem. Unlike the example of a squelch control noted above, where a user can adjust the squelch level based on experience and judgment, it is more difficult to program a computer system to automatically set a limit to differentiate between types of signals that are desirable and those that are not. For example, computers respond well to unambiguous input from keyboards, pointing devices, and similar input devices, but respond less satisfactorily to voice commands. Anyone who has used speech recognition programs has experienced some difficulty when the computer fails to recognize something the user said, which happens more often if there is any background noise or other sounds that affect the auditory input perceived by the computer.
Computer vision arguably is a much more intricate problem than speech recognition. If the computer must process too many visual signals or too broad a range of visual signals, the input will more likely be misread by the computer. On the other hand, if the computer suppresses too many visual signals, the computer also may misread visual inputs or ignore intended visual inputs entirely.
Today, computer vision is becoming an increasingly important field in furthering the desire to make computers and their interfaces even more user friendly. For example, the MIT Media Lab, as reported by Brygg Ullmer and Hiroshi Ishii in “The metaDESK: Models and Prototypes for Tangible User Interfaces,” Proceedings of UIST October 1997: 14-17,” has developed another form of “keyboardless” human-machine interface. The metaDESK includes a generally planar graphical surface that not only displays computing system text and graphic output, but also receives user input by “seeing” and responding to an object placed against the graphical surface. The combined object responsive and display capability of the graphical surface of the metaDESK is facilitated using IR lamps, an IR camera, a video camera, a video projector, and mirrors disposed beneath the surface of the metaDESK. The mirrors reflect the graphical image projected by the projector onto the underside of the graphical display surface to provide images that are visible to a user from above the graphical display surface. The IR camera can detect IR reflections from the undersurface of an object placed on the graphical surface. By “seeing” and detecting a specially formed object or IR-reflected light from an object disposed on a graphical display surface, the metaDESK can respond to the contemporaneous placement and movement of the object on the display surface to carryout a predefined function, such as displaying and moving a map of the MIT campus.
Others have been developing similar keyboardless interfaces. For example, papers published by Jun Rekimoto of the Sony Computer Science Laboratory, Inc., and associates describe a “HoloWall” and a “HoloTable” that display images on a surface and use IR light to detect objects positioned adjacent to the surface.
Both the metaDESK and HoloWall/HoloTable use IR light to see objects and movements for good reasons. If the systems responded to visible light, visible light projected by the systems and reflected back by the interactive surface could lead to false readings by the computing system. Further, even if reflections could be suppressed, unless the system is disposed in a dark room, room lights and other visible light passing through the interactive display surface would substantially adversely affect the computer vision systems.
Using reflected IR light to detect objects placed on an interactive display surface avoids much of the problems that would arise from attempting to recognize the objects with ubiquitous visible light. However, although people are generally aware of the IR content of light produced by most sources, because it is not visible to the naked eye, ambient IR light signals that might adversely impact computer vision systems also are very common. Incandescent lights, the sun, and a variety of other common sources generate IR light. These unintended IR signals, just like unintended visible light signals, can provide undesired input to IR-sensitive computer vision systems. Band-pass type filters can suppress visible light and other non-IR light, but they are not helpful in separating IR light reflected from an object that is to be detected from background IR light.
It is therefore desirable to filter, mask, or otherwise reduce the effects of unintended and undesired IR light signals, to prevent IR light vision systems from responding to extraneous IR light signals. The effect of the undesirable background IR light should be avoided when detecting objects without requiring that an IR computer vision system be operated in an environment that shields it from all background IR sources.